Databases replacing spreadsheets. MCP servers your team can query in plain language. Prediction models on top of your own sales history. Market intelligence that updates itself. Built specifically for groups with multiple subsidiaries, millions of rows, and zero appetite for off-the-shelf tools.
Off-the-shelf BI tools assume clean data, single entities, and patient IT teams. Enterprise groups have none of these. We build from what you actually have.
We take your exports — sales data, logistics feeds, CRM dumps, ERP outputs — and turn them into properly structured, queryable databases. Millions of rows. Historically reconciled. Updated automatically. Your team stops exporting to Excel the moment this is live.
MCP (Model Context Protocol) connects your databases to Claude and other AI tools. Your analysts ask questions in plain language. The AI queries the actual data. No dashboards to learn. No SQL required. Works inside Microsoft Teams.
We train prediction models directly on your historical sales, seasonality, and market signals — not on generic industry benchmarks. Reservation forecasting, inventory prediction, sales velocity by channel. Built on what actually happened in your business.
We build market intelligence databases from public sources — competitor pricing, product launches, distributor moves, alcohol market data, FMCG trends. Queryable through the same MCP interface as your internal data. Updated automatically.
We wire your campaign performance data directly to sales outcomes. Not click-through rates in isolation — actual revenue by campaign, by product, by channel. So when you increase spend on a region, you see what it moved, not just what it reached.
Competing subsidiaries can't share data — but the group still needs an overview. We build the architecture that maintains complete isolation between entities while giving group-level owners the summary view they need. Deployed for wine import groups with 2+ competing subsidiaries today.
A Nordic import group with two competing subsidiaries — each with full market data, sales history, and marketing operations — brought us in to build the intelligence layer from the ground up.
"Weekly Excel reports built manually by analysts. No shared query layer. No way to ask a question across the full product catalog without a two-day data pull."
Sales exports, logistics data, and market feeds structured into a unified database schema. 200M+ rows, historically reconciled, auto-refreshing.
Each entity gets its own MCP connector. Queries stay within the entity boundary. No cross-contamination. Group owner gets a separate aggregate view.
Seasonal demand forecasting trained on 8 years of actual sales data. Outputs feed directly into procurement planning and marketing budget allocation.
Competitor pricing, product launches, and distribution moves. Updated weekly. Queryable through the same interface as internal sales data.
Weekly intelligence summaries delivered via Teams. Meeting transcripts processed automatically. Action items extracted and distributed per entity.
The build is scoped per project. Ongoing operations run on a monthly retainer — one per subsidiary, scaling with scope. The compounding effect starts in month two.
We scope tight, deploy fast, and expand from there. No 6-month implementation cycles. No vendor dependencies. Your infrastructure, our build.
30 minutes. We assess your data landscape — what exists, what's manual, what decisions are currently made without good data. We tell you immediately if we're a fit.
One week. We map your data sources, identify quick wins and longer builds, and deliver a prioritized deployment plan with timelines and fixed project costs.
2–4 weeks. First module live — typically the core database plus MCP connector for one subsidiary. Your team starts using it before the full scope is complete.
Each subsequent subsidiary onboards faster. Data history grows. Models improve. Intelligence compounds. Month 12 is substantially more powerful than month 2.
We're selective because our deployment model requires it. One active build per new client until the first module is live.
Most groups have years of sales history, market data, and operational records that have never been properly structured or queried. One conversation to find out what's possible.
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